Leveraging Machine Learning for Crop Disease Detection and Prediction in African (Nigerian) Agriculture

Dr. ANYARAGBU Hope, Dr. OKORIE Emeka

Abstract


This study investigates the use of machine learning (ML) techniques for detecting and predicting crop diseases in Nigerian agriculture. With agriculture playing a vital role in Nigeria's economy and crop diseases posing significant challenges, the research assesses the effectiveness of various ML algorithms in reducing losses through early detection. It explores data collection methods, the modeling process, and the transformative potential of integrating ML systems into agricultural practices across Africa. The findings demonstrate the high accuracy achieved by machine learning algorithms, underscoring their feasibility for widespread implementation.

Keywords


Machine learning, 5G technology, disease detection, disease prediction.

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References


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DOI: http://dx.doi.org/10.52155/ijpsat.v48.1.6873

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